CN114757125A - Self-organizing heat sink structure design method based on diffusion back-diffusion system - Google Patents
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Abstract
The invention discloses a self-organizing heat sink structure design method based on a diffusion back-diffusion system, which comprises the following steps of 1: selecting an initial control field and a geometric initial value field; step 2: iterating the initial value field through a diffusion back-diffusion iteration equation to obtain a scalar function f and obtain a self-organization structure; and step 3: importing the geometric boundary information in the step 2 into CAD software, and converting the geometric boundary information into a geometric entity; and 4, step 4: evaluating the self-organization structure by computational fluid mechanics simulation; and 5: judging whether structural optimization is needed according to the heat transfer performance, if the structural optimization does not meet the design requirement, optimizing the control field and the geometric initial value field, and entering step 6; and if the design requirement is met, processing the heat sink structure. And 6: and (5) obtaining a new control field and an initial value field after optimization, and jumping to the step 2. The result shows that the method obviously improves the heat exchange capability of the heat sink under the condition of reducing the pressure loss of the heat sink, and has high application value.
Description
Technical Field
The invention relates to the technical field of engineering heat dissipation, in particular to a self-organizing heat sink structure design method based on a diffusion back-diffusion system.
Background
The heat sink is a device type widely applied to industrial equipment heat dissipation, mainly enhances the cooling effect by increasing the heat exchange area and strengthening convective heat transfer and heat conduction, and has important application in the fields of high-temperature power propulsion, electronic chips and the like. Two major indicators for evaluating heat sinks are heat exchange capacity and pressure loss. How to obtain the highest heat exchange capacity with the smallest possible pressure loss is the most important problem in the development process of heat sink technology and the bottleneck of the development of current heat sinks.
The heat sinks which are common at present have regular shapes, such as fins, fins and the like. Although the structure is convenient to manufacture, the comprehensive performance of the structure on heat exchange capacity and pressure loss is low, and a large promotion space is provided. In order to improve the comprehensive performance, the methods of improving the geometric characteristics, improving the heat exchanger material, exchanging heat through a micro-channel and the like can be adopted. Among these, improving the geometric characteristics is an improvement direction that has been widely studied because of the less cost required. The improvement of geometric characteristics is divided into two methods, one is to combine simple structures such as cylinders, straight ribs and the like to obtain a heat sink with better performance; the other is to construct a complex curve (surface) structure to take account of heat dissipation capacity and pressure loss. In the two methods, the construction of a complex curve (surface) structure has higher degree of freedom and can better approach the optimal structure in theory, so that the method is a promising method for improving the comprehensive capability of the heat sink by improving the geometrical characteristics.
However, the construction and control of multiple complex curves (surfaces) in the design domain have considerable difficulty, and the generation mechanism needs to be adjusted according to the distribution characteristics and the heat exchange characteristics of the flow field. Although the conventional density method, level set method and fractal algorithm can characterize complex structures, the conventional density method, level set method and fractal algorithm lack geometric constraint and geometric control means. These techniques do not support direct designer control of local dimensions, orientation, continuity, etc.
A self-organizing algorithm is a mathematical algorithm that generates and describes complex morphologies based on patterns that some living beings have in nature. The diffusion system with the source items can be used for generating the map speckle structure on some fishes, and has better controllability. In the existing research, the diffusion type self-organizing system can realize good approximation to the optimal structure in a very short time, and has the characteristics of low pressure loss and high heat exchange quantity. Based on the additive manufacturing technology, the construction of the heat sink through the self-organizing algorithm is a feasible way for improving the comprehensive performance of the heat sink, and has a good application prospect.
Accordingly, those skilled in the art have endeavored to develop a self-organizing heat sink structure design method based on a diffusion back-diffusion system.
Disclosure of Invention
In view of the above drawbacks of the prior art, the technical problem to be solved by the present invention is to provide a self-organizing geometry generation algorithm based on diffusion back-diffusion to simulate the structure of termite nest in nature, so as to introduce three different types of control fields, and generate a complex structure that cannot be described by a simple geometric language by adjusting the control fields and the initial geometric value fields. The heat sink structure generated based on the self-organizing method has high complexity while maintaining continuity, and has better heat exchange performance while reducing pressure loss compared with the traditional structure.
In order to achieve the purpose, the invention provides a self-organizing heat sink structure design method based on a diffusion back-diffusion system, which is characterized by comprising the following steps:
step 1: according to the use requirement of the heat sink, design indexes such as heat exchange coefficient, pressure drop and the like are determined, the omega of a design area and the inlet and the outlet of a flow channel are determined, and a group of initial control field and a group of initial geometric initial value field f are selected0；
Step 2: by diffusion back-diffusion iterative equation to geometric initial value field f0Iteration is carried out, a scalar function f in the design area is obtained after the convergence condition is met, and the self-organization structure is obtained through a phase field model method;
and step 3: importing the geometric boundary information in the step 2 into modeling software, converting the geometric boundary information into a geometric entity, and using the geometric entity for subsequent modeling simulation and processing;
and 4, step 4: performing computational fluid mechanics simulation on the obtained geometric entity to obtain heat exchange performance data of the heat sink, and evaluating the structural performance;
and 5: judging whether the structure needs to be optimized according to the heat transfer performance, if the structure does not reach the design index in the step 1, optimizing the control field and the geometric initial value field by adopting an optimization method, and entering a step 6; if the design requirements are met, processing the heat sink structure for practical use;
step 6: and (3) optimizing the control field and the geometric initial value field by adopting an optimization algorithm according to the defined problem, obtaining a new control field and a new geometric initial value field after optimization, and jumping to the step 2.
Further, the set of initial control fields of step 1 includes a structure size control field G, a structure anisotropy control field u, and a structure ratio control field k;
the structure size control field G is a scalar field with the same size as the design area and is used for controlling the size of the geometric structure, and the larger the value is, the larger the corresponding structure is; the structure anisotropy control field u is a vector field with the same size as the design area and is used for controlling the anisotropy of the structure, and the existence of the anisotropy field can enable the structure to extend along the direction determined by the u vector and control the trend of the fluid; the structural proportion control field k is a scalar field with the same size as the design area and used for controlling the ratio of fluid to solid in the design area, and the larger the value is, the larger the proportion of the fluid area is, otherwise, the larger the proportion of the solid is.
Further, the geometric initial value field f in the step 10Is a scalar field with the same size as the design area and the value range is [0, 1]]。
Further, the scalar function f in the step 2 is defined in a design area, and is obtained by iterative convergence of the geometric initial value field through a diffusion back-diffusion equation, and the value range is [0, 1 ].
Further, the diffusion back-diffusion iterative equation in step 2 includes two parts, which are an iterative function and a truncation function, respectively, where the specific form of the iterative function is:
wherein
And with
The coefficients of the diffusion term and the back diffusion term are respectively used for controlling the strength of the structural diffusion and the back diffusion;
is a gradient operator;
is the Hadamard product of the matrix;
is the kronecker product of the matrix; delta is an anisotropy coefficient, and the anisotropy proportion of the structure is controlled;
the specific form of the truncation function is: min (max (1, f), 0).
Further, the convergence iteration in the step 2 includes a convergence condition, the convergence condition includes two types, and the iteration number reaches an upper limit or an error of two iterations before and after the iteration is smaller than an allowable range; and stopping iteration after any one convergence condition is reached, wherein the upper limit of the iteration times and the allowable error range are set according to specific problems.
Further, the specific method of the phase-field model method in step 2 is as follows: boundary threshold f for a scalar function field f and a defined pair*E (0, 1), and f is f*The point set of composition is used as the boundary of the structure, and f is larger than f*The formed point set is used as the outer part of the structure, and f is less than f*The composed set of points is taken as the interior of the structure.
Furthermore, the geometric boundary information in the step 3 includes a point set forming a boundary, and is imported into modeling software to be converted into an editable geometric entity.
Further, in the computational fluid dynamics simulation of step 4, a k-epsilon turbulence model and an enhanced wall surface condition are adopted, corresponding inlet and outlet conditions are set according to working conditions, and related parameters are set.
Further, the design requirement in the step 5 includes two parts: surface temperature distribution and pressure loss; wherein, the surface temperature distribution can be expressed by a dimensionless number Nu, and the highest temperature of the structure surface is considered; the pressure loss can be represented by a dimensionless number CfThe representation is carried out, and the practical situation is comprehensively considered according to the specific working conditions and requirements;
the processing mode of processing the heat sink structure in the step 5 comprises an additive manufacturing technology; the technology can be used for manufacturing metal parts with complex structures, and a proper processing mode is selected according to specific materials in practice.
The optimization algorithm of the step 6 comprises a adjoint optimization method and a proxy model method.
The invention has the beneficial effects that:
(1) the self-organization method based on diffusion back diffusion can control the size, the orientation and the continuity of the heat sink structure at any position in a calculation domain to form the heat sink structure which has small volume, large surface area and complex geometric shape and can guide the flow field distribution;
(2) experiments show that the heat sink structure designed based on the self-organization method has pressure loss obviously smaller than that of the traditional pin fin array structure, and the heat exchange capability is greatly improved;
(3) simulation results show that the heat sink structure designed by the self-organization method has more reasonable flow field distribution, has good heat flow synergistic characteristics, and can improve the heat exchange capacity while reducing pressure loss;
(4) compared with other optimization design methods such as topology optimization and the like, the heat sink structure obtained by the self-organization method has good continuity, does not have suspended matters or fragments, and has good processability
The conception, the specific structure and the technical effects of the present invention will be further described with reference to the accompanying drawings to fully understand the objects, the features and the effects of the present invention.
Drawings
FIG. 1 is a flow chart of a self-organizing heat sink design algorithm based on a diffusion back-diffusion system;
FIG. 2 is a schematic diagram of the composition, structure and import/export information of a designed heat sink;
FIG. 3 is a schematic diagram of a final iteration result of a self-organizing algorithm based on a diffusion back-diffusion system;
FIG. 4 is a diagram of a self-organizing algorithm design heat sink digital model;
FIG. 5 is a schematic diagram of a self-organizing algorithm design heat sink structure meshing;
fig. 6 is a graph of the experimental result of the highest surface temperature of the conventional heat sink structure and the heat sink designed by the self-organizing algorithm under a certain working condition.
Detailed Description
The technical contents of the preferred embodiments of the present invention will be more clearly and easily understood by referring to the drawings attached to the specification. The present invention may be embodied in many different forms of embodiments and the scope of the invention is not limited to the embodiments set forth herein.
In the drawings, elements that are structurally identical are represented by like reference numerals, and elements that are structurally or functionally similar in each instance are represented by like reference numerals. The size and thickness of each component shown in the drawings are arbitrarily illustrated, and the present invention is not limited to the size and thickness of each component. The thickness of the components has been exaggerated in some places in the drawings where appropriate for clarity of illustration.
Example 1
As shown in FIG. 1, the invention provides a self-organizing heat sink structure design method based on a diffusion back-diffusion system, which specifically comprises the following steps:
step 1: and determining the design area and the inlet and the outlet of the heat sink according to the working conditions and requirements of the heat sink. The situation of this embodiment is: the gas flows in parallel from opposite corners. The dimension of the heat sink area is L which is 50mm, and the width of the inlet and the outlet is 1/5L. For the convenience of processing, the heat sink is composed of two partsWherein the base portion has a height h0The design is not possible at 3m, and the design part height h is 5mm, and the geometric design is possible, and the design area, the access and some geometric information are marked in fig. 2. According to the design experience in the previous stage, the control field and the geometric initial field are given before iteration, and in view of simplifying the model, k is taken as a constant 0.15 in the embodiment. The numerical calculation requires the design area to be gridded, and the grid is divided into a 64 × 64 square grid in the present embodiment.
Step 2: and (4) substituting the three control fields given in the step 1 and the geometric initial field into an iteration equation for iteration. Specifically to this embodiment, the specific boundary conditions are:
the final iteration result of this example is shown as self-organizing structure 1 in fig. 3. It can be seen that the self-organizing generating structure has more complicated geometric features than the traditional structure, and cannot be described by a simple geometric language.
And 3, step 3: some points on the set boundary can be found by the contour command in MATLAB, and the composed curve is closed. The SolidWorks can be used for importing and generating corresponding curves, and can be converted into editable entities in a sketch. The relevant geometric digital model is shown in fig. 4.
In order to make a certain partial area not generate any geometrical structure, a masking operation can be carried out: after each iteration is completed, the scalar function f value in the non-design area is set to be 0, and finally, a geometric structure cannot be generated in the area in the structure.
And 4, step 4: first, heat sink entities are generated by SolidWorks and the corresponding fluid domains are plotted. And converting into stp format and importing into Fluent for grid division. The rule of the grid division of the present embodiment is as follows: the grid size of the solid domain and the fluid domain is 0.35mm, the fluid domain is added with boundary layers on other surfaces except the inlet and outlet sections so as to solve the flow more accurately, and the specific parameters are as follows: the number of layers is 21, the growth rate is 1.2, and the transition rate is 0.272. Fixing deviceThe body region added 1 layer of boundary layer at all sides except the base side to facilitate the thermal conductivity calculation, the transition rate was also 0.272. The result of the mesh division in this embodiment is shown in fig. 5. After the grid division is finished, the independence of the grid and the y + are required to be checked to ensure the rationality of the grid division, in the embodiment, the number of the grids is converged in 800 ten thousands of time, most of the area y + is less than 1, and the related requirements are met. The calculation model adopts a model capable of realizing k-epsilon turbulence and an enhanced wall surface condition, wherein the boundary condition needs to be designed according to specific problems, and the relevant settings in the embodiment are as follows: the inlet mass flow is 0.007183kg/s, the outlet pressure is 1 atmospheric pressure, and the uniform distribution size of the bottom surface of the heat sink is 4000W/m2The heat flux density of (1). After the simulation is finished, the heat transfer performance of the simulation system is analyzed by calculating the surface temperature distribution and the inlet and outlet pressure change, and the pressure loss performance of the simulation system is analyzed by calculating the inlet and outlet pressure intensity, so that the performance is comprehensively evaluated. While surface fluid flowgrams are derived for subsequent analysis.
And 5: calculating Nu and pressure loss coefficient CfThe formula of (1) is as follows:
wherein h iscIs the average convective heat transfer coefficient, TiAnd ToRespectively inlet and outlet temperatures, DhThe hydraulic diameter of the inlet and outlet is shown, lambda is the air heat conductivity coefficient, rho is the air density, delta p is the inlet and outlet pressure difference, and U is the inlet speed.
The heat sink structure designed by the Selective Laser Melting (SLM) technology is processed, the processing material is 316L, the processing precision is 0.3mm, and a processed finished product has no crack and flaw and meets the working requirements.
Example 2
This example is identical to example 1 except that the three control fields are different. Nu 297.35; cf is 12.90; nu 301.48; cf is 12.73; nu 348.74; cf is 10.02. The results obtained are shown in fig. 3 for self-organizing structure 2.
Example 3
This example is identical to example 1 except that the three control fields are different. Nu 272.68; cf ═ 8.08; nu 323.36; cf ═ 7.36; nu 396.88; cf is 5.62. The results obtained are shown in fig. 3 for self-organizing structure 3.
In order to understand the specific control effect of the three control fields introduced in the invention, the invention explores the influence of the three control fields on the formation of the final structure by changing the three control fields. For the structure size control field G, when the value of G is larger, the generated structure is also larger; when the distribution of G in space is not constant, the structure size also changes accordingly. For a structure anisotropy control field u, the structure will extend in the direction of the u-field at the location. The structure proportion control field k is used for controlling the proportion of fluid and solid in the design area, and when the value of k is larger, the proportion of fluid in the design area is larger, otherwise, the proportion of solid is larger. This shows that the introduction of three control fields can achieve very good control of various aspects of the geometry without losing adjustability while increasing the complexity of the structure.
In order to further understand the heat exchange performance and the engineering practicability of the heat sink, the heat sink is verified through the self-organization structure in the three embodiments, the surface temperature distribution and the pressure loss of the heat sink are measured in an experimental mode, and the surface temperature distribution and the pressure loss are compared with those of the traditional structure. At a flow rate of 20m3The maximum temperature distribution of the surface temperature of each structure under the condition that the heating power is 15W is shown in FIG. 6; nu and C of structure obtained by calculation under various working conditionsfAs shown in table 1.
TABLE 1
The results show that the heat sink structure obtained by the self-organizing manner has lower surface average temperature and obviously reduced hot zone range compared with the traditional regular-shaped heat sink structure. The maximum temperature is also significantly reduced compared to conventional structures. From the angle of dimensionless number, the self-organizing structure can remarkably reduce the pressure loss of the heat sink structure and obtain better heat exchange performance while maintaining and even improving the heat exchange capability. According to the simulation result, the self-organization sends the designed turbulent flow column structure, the number of vortexes at the tail part is small, and the pressure loss is favorably reduced; the flow and heat cooperativity is better, the fluid distribution is more uniform, and the structure heat dissipation is facilitated.
Therefore, compared with the traditional structure, the self-organizing design scheme provided by the invention has obvious advantages, and the pressure loss can be obviously reduced while the heat exchange capacity is improved.
The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.
Claims (10)
1. A self-organizing heat sink structure design method based on a diffusion back-diffusion system is characterized by comprising the following steps:
step 1: determining design indexes such as heat exchange coefficient, pressure drop and the like according to the use requirement of the heat sink, determining the design area omega and the inlet and the outlet of a flow channel, and selecting a group of initial control fields and geometric initial value fields f0；
Step 2: by diffusion back-diffusion iterative equation to geometric initial value field f0Carry out iteration to fullObtaining a scalar function f in the design area after the conditions are sufficiently converged, and obtaining a self-organization structure by a phase-field model method;
and step 3: importing the geometric boundary information in the step 2 into modeling software, converting the geometric boundary information into a geometric entity, and using the geometric entity for subsequent modeling simulation and processing;
and 4, step 4: performing computational fluid mechanics simulation on the obtained geometric entity to obtain heat exchange performance data of the heat sink, and evaluating the structural performance;
and 5: judging whether the structure needs to be optimized according to the heat transfer performance, if the structure does not reach the design index in the step 1, optimizing the control field and the geometric initial value field by adopting an optimization method, and entering a step 6; if the design requirements are met, processing the heat sink structure for practical use;
step 6: and (3) optimizing the control field and the geometric initial value field by adopting an optimization algorithm according to the defined problem, obtaining a new control field and a new geometric initial value field after optimization, and jumping to the step 2.
2. The design method of self-organizing heat sink structure based on diffusion back-diffusion system as claimed in claim 1, wherein the set of initial control fields of step 1 includes structure size control field G, structure anisotropy control field u and structure proportion control field k;
the structure size control field G is a scalar field with the same size as the design area and is used for controlling the size of the geometric structure, and the larger the value is, the larger the corresponding structure is; the structure anisotropy control field u is a vector field with the same size as the design area and is used for controlling the anisotropy of the structure, and the existence of the anisotropy field can enable the structure to extend along the direction determined by the u vector and control the trend of the fluid; the structural proportion control field k is a scalar field with the same size as the design area and used for controlling the ratio of fluid to solid in the design area, and the larger the value is, the larger the proportion of the fluid area is, otherwise, the larger the proportion of the solid is.
3. The self-organizing heat sink structure based on a diffuse back-diffusion system as claimed in claim 1The design method is characterized in that the geometric initial value field f in the step 10Is a scalar field with the same size as the design area and the value range is [0, 1]]。
4. The method as claimed in claim 1, wherein the scalar function f in step 2 is defined in a design area, and is obtained by iterative convergence of the geometric initial value field through a diffusion back-diffusion equation, and the value range of the scalar function f is [0, 1 ].
5. The method according to claim 1, wherein the iterative diffusion back-diffusion equation in step 2 includes two parts, namely an iterative function and a truncation function, where the iterative function is specifically in the form of:
wherein
And
the coefficients of the diffusion term and the back diffusion term are respectively used for controlling the strength of the diffusion and the back diffusion of the structure;
is a gradient operator;
is the Hadamard product of the matrix;
is the kronecker product of the matrix; delta is an anisotropy coefficient, controlThe anisotropic ratio of the structure;
the specific form of the truncation function is: min (max (1, f), 0).
6. The design method of self-organizing heat sink structure based on diffusion back-diffusion system as claimed in claim 1, wherein said convergence iteration in step 2 includes convergence conditions, said convergence conditions include two types, the number of iterations reaches the upper limit or the error of two iterations is smaller than the allowable range; and stopping iteration after any one convergence condition is reached.
7. The method for designing a self-organized heat sink structure based on a diffusion back-diffusion system as claimed in claim 1, wherein the phase field model method of step 2 is as follows: boundary threshold f for a scalar function field f and a defined pair*E (0, 1), and f is f*The point set of composition is used as the boundary of the structure, and f is larger than f*The formed point set is used as the outer part of the structure, and f is less than f*The composed set of points is taken as the interior of the structure.
8. The method as claimed in claim 1, wherein the geometric boundary information in step 3 includes a set of points forming a boundary, and the set of points is imported into modeling software and converted into an editable geometric entity.
9. The method according to claim 1, wherein in the computational fluid dynamics simulation of step 4, a k-epsilon turbulence model and enhanced wall conditions are adopted, and corresponding inlet and outlet conditions and related parameters are set according to working conditions.
10. The method as claimed in claim 1, wherein the design requirement in step 5 includes two parts: surface ofTemperature distribution and pressure loss; wherein, the surface temperature distribution can be expressed by a dimensionless number Nu, and the highest temperature of the structure surface is considered; the pressure loss can be represented by a dimensionless number CfThe representation is carried out, and the practical situation is comprehensively considered according to the specific working conditions and requirements;
the processing manner of processing the heat sink structure in the step 5 comprises an additive manufacturing technology.
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| CB03 | Change of inventor or designer information | ||
| CB03 | Change of inventor or designer information |
Inventor after: Yang Li Inventor after: Yu Baicheng Inventor after: Lu Zijie Inventor after: Wang Xinxing Inventor after: Wang Binyan Inventor before: Yang Li Inventor before: Yu Baicheng Inventor before: Lu Zijie Inventor before: Wang Xinxing Inventor before: Wang Binyan |